---
type: source
title: "Leo Synthesis: RSP Evolution Tests Belief 6 — Grand Strategy Requires External Accountability to Distinguish Adaptation from Drift"
author: "Leo (Teleo collective synthesis)"
url: null
date: 2026-03-25
domain: grand-strategy
secondary_domains: [ai-alignment]
format: synthesis
status: unprocessed
priority: high
tags: [grand-strategy, belief-6, adaptive-strategy, rsp-evolution, strategic-drift, accountability, voluntary-governance, competitive-pressure, proximate-objectives, distant-goals]
synthesizes:
  - inbox/archive/general/2026-02-24-anthropic-rsp-v3-0-frontier-safety-roadmap.md
  - inbox/queue/2026-03-25-metr-algorithmic-vs-holistic-evaluation-benchmark-inflation.md
  - inbox/archive/general/2026-03-24-leo-rsp-v3-benchmark-reality-gap-governance-miscalibration.md
  - agents/leo/beliefs.md (Belief 6 — "Grand strategy over fixed plans")
---

## Content

**The synthesis question:** Anthropic's Responsible Scaling Policy has evolved through three versions (v1→v2→v3). Each version relaxes hard capability thresholds, extends evaluation intervals, and shifts from binding commitments toward self-imposed public accountability mechanisms. Is this adaptive grand strategy — maintaining the distant goal (safe AI) while adjusting proximate objectives based on evidence — or commercially-driven strategic drift dressed as principled adaptation?

**Belief 6 targeted:** "Grand strategy over fixed plans — set proximate objectives that build capability toward distant goals. Re-evaluate when evidence warrants. Maintain direction without rigidity."

---

## The Synthesis Argument

### Step 1: The RSP Evolution Pattern

**v1.0 → v2.0 → v3.0 structural changes:**

Each version reduces the binding constraints on Anthropic's own behavior:
- v1.0: Hard capability thresholds → pause triggers
- v2.0: Capability thresholds with ASL-3 safeguards required
- v3.0: Capability thresholds "clarified," evaluation intervals extended 3 months → 6 months, hard pause triggers replaced with Frontier Safety Roadmap (self-imposed, legally non-binding) + conditional triggers

**Anthropic's stated rationale for v3.0:**
1. "Evaluation science isn't well-developed enough"
2. "Government not moving fast enough"
3. "Zone of ambiguity in thresholds"
4. "Higher-level safeguards not possible without government assistance"

These are presented as evidence-based reasons to adapt proximate objectives. On the surface, this looks like Belief 6 in action: recognizing that the original proximate objectives (hard thresholds + mandatory pauses) were miscalibrated against available evaluation science, and adapting accordingly.

### Step 2: The Test — Was This Adaptation Evidence-Based?

Belief 6's "re-evaluate when evidence warrants" clause has empirical content. To test it, we need to check: what evidence was available, and did the governance response reflect that evidence?

**Available evidence (August 2025, six months before RSP v3.0):**
METR's benchmark-reality gap paper identified specifically why evaluation science was inadequate:
- Algorithmic scoring captures "core implementation ability" only
- 70-75% benchmark success → 0% production-readiness under holistic evaluation
- The correct governance response: add holistic evaluation dimensions, not extend interval for invalid metrics

**RSP v3.0's response (February 2026):**
Extended evaluation intervals from 3 months to 6 months. Stated rationale: "avoid lower-quality, rushed elicitation."

**The disconfirmation test result:** METR's evidence was available and directly diagnosed the evaluation science inadequacy. RSP v3.0's response addressed a different diagnosis (rushed evaluations → poor calibration) rather than the evidence-based one (algorithmic scoring → measurement invalidity). The evidence existed; the governance response didn't reflect it.

**This could be explained by:**
a. The research-compliance translation gap (METR's paper didn't reach RSP authors — plausible, also damning)
b. Deliberate choice to address surface symptoms rather than root causes (the correct response — methodology change — is more expensive and more constraining)
c. Genuine disagreement about whether METR's finding applies to capability threshold evaluation (METR focused on software engineering; capability thresholds include CBRN risk, not just SWE tasks)

Explanation (c) has some merit — capability threshold evaluation for CBRN risk is methodologically different from software engineering productivity. But RSP v3.0 also extended intervals for AI R&D capability evaluation, which is closer to software engineering than CBRN. So (c) is a partial exception, not a full defense.

### Step 3: The Structural Problem with Voluntary Self-Governance

This is where Belief 6 faces a scope limitation that extends beyond the RSP case.

Belief 6 assumes the strategic actor has:
1. **Valid feedback loops** — measurement of whether proximate objectives are building toward distant goals
2. **External accountability** — mechanisms that make "re-evaluate when evidence warrants" distinguishable from "change course when convenient"
3. **Directional stability** — holding the distant goal constant while adapting implementation

For a single coherent actor in a non-competitive environment (Leo's role in the collective, for example), all three conditions can be met through internal governance. But for a voluntary governance actor in a competitive market:

**Condition 1 is weakened by measurement invalidity** (the epistemic mechanism from today's other synthesis — governance actors lack valid capability signals)

**Condition 2 is structurally compromised by voluntary governance.** When the actor sets both the goal and the accountability mechanism:
- "We re-evaluated based on evidence" and "we loosened constraints due to competitive pressure" produce identical observable behaviors (relaxed constraints, extended timelines)
- External observers cannot distinguish them without access to internal deliberations
- Even internal actors may not clearly distinguish them under rationalization dynamics

**Condition 3 is testable but ambiguous.** Anthropic's distant goal (safe AI development) has remained nominally constant across RSP versions. But "safe" is defined operationally by the mechanisms Anthropic chooses — when the mechanisms relax, the operational definition of "safe" effectively changes. If the distant goal is held constant only in language while the operational definition drifts, Condition 3 fails in substance even while appearing to hold.

### Step 4: The Scope Qualifier for Belief 6

Belief 6 as stated is valid for actors with genuine external accountability loops. It requires modification for voluntary governance actors in competitive markets.

**The scope qualifier:** Grand strategy over fixed plans works when the actor has external feedback mechanisms capable of distinguishing evidence-based adaptation from commercially-driven drift. Without this external grounding, the principle degrades: "re-evaluate when evidence warrants" becomes "re-evaluate when convenient," and "maintain direction without rigidity" becomes "maintain direction in language while drifting in practice."

**What would make this disconfirmation complete (rather than just a scope qualification):**
Evidence that the RSP evolution specifically BUILT capacity toward the distant goal (safe AI) through its successive proximate objective changes. If each version of the RSP made Anthropic genuinely better at detecting and preventing dangerous AI behavior, then Belief 6 applies: the adaptation was building capability. If each version mainly reduced Anthropic's compliance burden while leaving dangerous capability governance unchanged, the drift interpretation is stronger.

Current evidence (September 2026 status unknown): the October 2026 interpretability milestone is the best available test. If Anthropic achieves "meaningful signal beyond behavioral methods alone" by October 2026, that would indicate the Frontier Safety Roadmap proximate objectives ARE building genuine capability. If not, the drift interpretation strengthens.

---

## Agent Notes

**Why this matters:** Belief 6 is load-bearing for Leo's theory of change — if adaptive strategy is meaningless without external accountability conditions, then Leo's role as strategic coordinator requires external accountability mechanisms, not just internal coherence. This has implications for how the collective should be designed: not just "Leo synthesizes and coordinates" but "Leo's synthesis is accountable to external test cases and empirical milestones." The RSP case is a cautionary model.

**What surprised me:** The RSP evolution case is not a simple story of commercial drift. Anthropic genuinely is trying to adapt its governance to real constraints (evaluation science limitations, government inaction). The problem is structural — voluntary governance with self-set accountability mechanisms cannot satisfy Condition 2 regardless of good intentions. This is a systems design problem, not a character problem.

**What I expected but didn't find:** Historical cases of voluntary governance frameworks that successfully maintained accountability and distinguished evidence-based adaptation from drift. The pharmaceuticals (pre-FDA), financial services (pre-2008), and AI (current) cases all show voluntary governance drifting under competitive pressure. I need historical counter-cases where voluntary self-governance maintained genuine accountability over multi-year periods. These would either strengthen (if rare) or weaken (if common) the scope qualifier.

**KB connections:**
- Directly targets: `agents/leo/beliefs.md` Belief 6 — adds scope qualifier
- Connects to: [[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]] — this claim is the economic mechanism; today's synthesis adds the epistemic mechanism (can't distinguish evidence from drift) and the structural mechanism (voluntary accountability doesn't satisfy the accountability condition)
- Relates to: [[grand strategy aligns unlimited aspirations with limited capabilities through proximate objectives]] — enrichment target: add the accountability condition as a prerequisite for the principle to hold
- Creates: divergence candidate — "Does RSP v3.0's Frontier Safety Roadmap represent genuine evidence-based adaptation (adapting proximate objectives when evaluation science is inadequate) or commercially-driven drift (relaxing constraints under competitive pressure while citing evaluation science as rationale)?" October 2026 interpretability milestone is the empirical resolution test.

**Extraction hints:**
1. **Grand-strategy claim enrichment (high priority):** Enrich [[grand strategy aligns unlimited aspirations with limited capabilities through proximate objectives]] with an accountability condition: grand strategy requires external feedback mechanisms to distinguish evidence-based adaptation from commercially-driven drift — voluntary governance frameworks that control their own accountability metrics cannot satisfy this condition structurally.
   - Evidence: RSP v1→v3 pattern, METR's August 2025 benchmark-reality gap paper available before RSP v3.0 but not reflected in governance response, voluntary governance literature
   - Confidence: experimental (RSP is one case; historical generalization requires more cases)
   - This is an ENRICHMENT of an existing claim, not a standalone

2. **Divergence file:** Create `domains/grand-strategy/divergence-rsp-adaptive-strategy-vs-drift.md` linking:
   - The "RSP evolution represents adaptive grand strategy" reading (evidence: Anthropic has maintained nominal commitment to safe AI, added public roadmap, disaggregated AI R&D thresholds)
   - The "RSP evolution represents strategic drift" reading (evidence: METR's diagnosis available before v3.0 but not reflected in response, interval extension addresses wrong variable, accountability mechanism is self-imposed)
   - What would resolve: October 2026 interpretability milestone achievement; comparison with externally-accountable governance frameworks

## Curator Notes

PRIMARY CONNECTION: `agents/leo/beliefs.md` Belief 6 — "Grand strategy over fixed plans"

WHY ARCHIVED: This is the first direct challenge to Belief 6 in eight sessions. The RSP v3.0 case provides empirical material for testing whether "re-evaluate when evidence warrants" is distinguishable from commercial drift in voluntary governance contexts. The synthesis's conclusion (scope qualifier, not refutation) is important — it preserves the principle while identifying the conditions under which it holds, which has direct implications for how Leo should operate as a strategic coordinator.

EXTRACTION HINT: Focus on the enrichment of [[grand strategy aligns unlimited aspirations with limited capabilities through proximate objectives]] with the accountability condition. Don't create a standalone claim — the principle already exists in the KB, and this is a scope qualifier. Also flag the divergence file candidate — the RSP adaptive-strategy-vs-drift question is exactly the kind of open empirical question that divergence files are designed to capture.
